Assoc, AI Core DevOps Engineer, Data Platform, Group Technology

Job Responsibility Working with subject-matter experts (SMEs) across finance, infrastructure, security, risk, and application teams, you will learn their processes and constraints to design AI and agent-based solutions that give the organisation clear, actionable insight. We want a resource who takes full ownership of their work and is keen to learn how enterprise architecture comes together. Enterprise 360° AI Initiative • Work with SMEs across domains to map their current processes, data sources, pain points, and limitations. • Turn business needs into AI and agentic use cases, then propose, prototype, and refine solutions with the team. • Develop AI models for cost forecasting, anomaly detection, utilisation right-sizing, and compliance risk scoring. • Design and build AI agents that can answer questions, summarise posture, flag issues, and recommend or trigger actions (for example, “Which applications are over-provisioned and missing DR coverage?”). • Put guardrails, evaluation, human-in-the-loop approvals, and audit trails in place so agents are safe and trustworthy at enterprise scale. • Turn successful prototypes into reusable, production-grade services and reference patterns. Full-Stack Application Development • Build and maintain interactive React-based dashboards and tools that surface AI-driven insights to business users, including data visualisation with charting libraries. • Develop and extend Python/Flask RESTful APIs that integrate with databases, AI services, and external data sources, with attention to error handling, caching, and security. • Work across the full stack—from responsive, user-facing UIs to backend SQL query generation, API design, and server-side business logic. Architecture and Stakeholder Engagement • Contribute to group-wide initiatives as part of the Architecture team, from early assessment to delivery. • Help write solution designs, reference architectures, technical standards, and decision records. • Present findings, recommendations, and trade-offs clearly to both technical and business audiences. AI Platform Engineering (GCP and On-Prem) • Build CI/CD and MLOps pipelines for models, agents, and microservices, deploying to GKE and on-prem clusters. • Deploy and scale model and LLM serving (for example vLLM, Triton, or KServe) and Vertex AI endpoints. • Integrate with GitOps (ArgoCD or Flux) and observability platforms (Prometheus, Grafana, Cloud Monitoring, OpenTelemetry). • Apply security and compliance standards across all deployments. Ownership & Execution • Own your deliverables end to end: plan, build, document, hand over, and support them. • Take initiative, raise risks early, suggest improvements, and follow through without being asked. • Keep up with developments in AI, agents, and infrastructure, and bring useful ideas back to the team. Job Requirements • 3-6 years of experience in DevOps, platform, MLOps, or AI engineering. • Hands‑on experience building ML models or LLM-based applications in Python. • Exposure to RAG pipelines, vector databases, LLM evaluation, and guardrails.Exposure to agentic frameworks and patterns such as LangGraph, Google ADK, Vertex AI Agent Builder, CrewAI, tool/function calling, or MCP. • Experience building interactive web applications with React (hooks, context, component composition) and modern JavaScript/ES6+, including data visualisation with charting libraries such as Recharts or Chart.js. • Hands‑on backend development with Python/Flask (or FastAPI/Django), building RESTful APIs that integrate with databases (MySQL, Trino/Presto) and external services, with attention to error handling, caching, and security.Comfortable working across the full stack—from designing responsive, user-facing dashboards and forms (Bootstrap, styled-components) to implementing API endpoints, SQL query generation, and server-side business logic. • Hands‑on GCP experience (GKE, Vertex AI, BigQuery, IAM) and experience with self-managed Kubernetes. • Solid SQL and data‑wrangling skills for pulling together data from many enterprise sources. • The confidence to engage SMEs, ask good questions, and turn their processes into technical solutions. • A strong sense of ownership, accountability, and follow-through.Clear written and verbal communication, alongside a genuine curiosity to learn enterprise architecture. Location: DBS Asia Hub Job: Technology Schedule: Regular Employee Status: Full time #J-18808-Ljbffr